Patrizia Bolzan, Francesca Zeccara, Massimo Bianchini
et al.
The Circular Sofa Platform (CSP) project aims to foster an effective and systemic circular transition in the Italian upholstered furniture sector. Through a modular and context-sensitive design platform, it brings together strategies across materials, processes, and supply chains. Its integrated, multi-level approach demonstrates the flexibility of design when applied to specific regulatory and production systems. The methodology adopted shows how design can actively interpret and enable sustainable transition within complex industrial contexts.
The introduction of ultraviolet (UV) light technologies to the graphic arts industry has revolutionised printing by offering better print quality, faster curing times and the ability to print on a variety of substrates. Despite these advances, UV light and UV-curable materials pose significant health risks to workers. This paper examines the potentially harmful effects of UV light on workers in the graphics technology sector and outlines key safety measures to mitigate these risks. The UV spectrum (100–400 nm) is categorised as UVA, UVB and UVC. While UVA and UVB are partially absorbed by the atmosphere, UVC is almost completely absorbed by the ozone layer. In graphics technology, however, artificial UV light sources can expose workers to harmful radiation. The increasing use of UV light in UV printing and UV curing requires a closer look at occupational hazards. Harmful effects include skin damage (erythema, skin ageing, pigmentation changes, skin cancer) and eye damage (photokeratitis, cataracts, retinal damage). UV-curable inks and coatings also contain photoinitiators and chemicals that pose health risks (irritation, allergic reactions and respiratory problems) and require comprehensive safety protocols. Key safety measures include personal protective equipment (PPE) such as protective clothing, goggles and respirators. Technical measures such as UV-blocking shields, covers and adequate ventilation reduce exposure. Comprehensive training, the use of PPE, safety protocols and regular inspections ensure the safety of employees. By addressing the risk of UV exposure, the industry can protect its employees while continuing to innovate.
Erik Ciravegna, Ludovica Rosato, Mariapaola Puglielli
et al.
This paper explores the potential of design to drive circular transitions in the Made in Italy fashion system, with a particular focus on digital innovation and packaging as a strategic interface for circularity and sustainability. To address contemporary challenges—such as environmental degradation, regulatory shifts, and digital transformation—this work aims to reframe packaging from a technical object to a multidimensional artefact that supports knowledge exchange, encourages collaboration across sectors, and helps stakeholders make informed decisions. By combining systemic and advanced design approaches, the study investigates how smart packaging can align technological innovation with ethical responsibility, promoting transparency, traceability, and value regeneration. The research includes an experimental project involving a group of universities and companies from the fashion, packaging, and information technology sectors. Using a co-design methodology, the project developed a smart, reusable packaging prototype incorporating blockchain infrastructure. This solution responds to both logistical and communication needs while anticipating and aligning with upcoming European sustainability policies such as the Digital Product Passport. This paper shows how theoretical insights can be connected with applied innovation to highlight the central role of design in steering systemic transitions. Smart packaging, therefore, can be seen as a catalyst for distributed innovation, serving as a bridge between physical systems, digital tools, and cultural values across the fashion supply chain.
Klaus Regenauer-Lieb, Manman Hu, Hui Tong Chua
et al.
The static topology of surface characteristics and active sites in catalysis overlooks a crucial element: the dynamic processes of optimal pattern formation over time and the creation of intermediate structures that enhance reactions. Nature’s principle of coupling reaction and motion in catalytic processes by enzymes or higher organisms offers a new perspective. This work explores a novel theoretical approach by adding the time dimension to optimise topological variations using the Maximum Entropy Production (MEP) assumption. This approach recognises that the catalyst surface is not an unchanging energy landscape but can change dynamically. The time-dependent transport problem of molecules is here interpreted by a non-equilibrium model used for modelling and predicting dynamic pattern formation in excitable media, a class of active matter requiring an activation threshold. We present a nonlocal reaction–cross-diffusion (RXD) formulation of catalytic reactions that can capture the catalyst’s interaction with the target molecule in space and time. The approach provides a theoretical basis for future deep learning models and multiphysics upscaling of catalysts and their support structures across multiphysics fields. The particular advantage of the RXD approach is that it allows each scale to investigate dynamic pattern-forming processes using linear and nonlinear stability analysis, thus establishing a rule base for developing new catalysts.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
Our project, part of the Play Alghero initiative funded by the EU's MedGaims program, delves into the intersection of design's role as a catalyst in representing local identities and explores gamification as a strategy to promote heritage and enhance territorial attractiveness. Structured as a series of physical installations throughout the town's historic center connecting to the city’s airport and outskirts, our project combines a distinctive visual identity with playful interactions to engage users in exploring both the tangible and intangible aspects of the city of Alghero. Designed to create interactions between people and places, a playful itinerary interprets the local identity, encouraging both tourists and locals to reflect on the sense of place.
The architecture, engineering, and construction (AEC) industry still heavily relies on information stored in drawings for building construction, maintenance, compliance and error checks. However, information extraction (IE) from building drawings is often time-consuming and costly, especially when dealing with historical buildings. Drawing search can be simplified by leveraging the information stored in the title block portion of the drawing, which can be seen as drawing metadata. However, title block IE can be complex especially when dealing with historical drawings which do not follow existing standards for uniformity. This work performs a comparison of existing methods for this kind of IE task, and then proposes a novel title block detection and IE pipeline which outperforms existing methods, in particular when dealing with complex, noisy historical drawings. The pipeline is obtained by combining a lightweight Convolutional Neural Network and GPT-4o, the proposed inference pipeline detects building engineering title blocks with high accuracy, and then extract structured drawing metadata from the title blocks, which can be used for drawing search, filtering and grouping. The work demonstrates high accuracy and efficiency in IE for both vector (CAD) and hand-drawn (historical) drawings. A user interface (UI) that leverages the extracted metadata for drawing search is established and deployed on real projects, which demonstrates significant time savings. Additionally, an extensible domain-expert-annotated dataset for title block detection is developed, via an efficient AEC-friendly annotation workflow that lays the foundation for future work.
Colorants used in security inks are special pigments that radiate in the UV region or IR region. Obtained pigments can be from valuable rare earth elements or they can be organic based. Organic-based pigments are generally insoluble in water, which limits their use. For this purpose, an organic based UV-radiating pigment was synthesized and made water-soluble by forming its salt. With the obtained salt-formed pigment, inkjet ink that can be used in counterfeiting was applied and its printability and resistance properties were determined. In this study, 1, 3, 6, 8-pyrene sulfonic acid tetrasodium salt was synthesized and water-based inkjet inks with hydroxy ethyl cellulose binder were produced. The prepared inks were printed on the paper surface. The color and gloss of the prints obtained were measured both in the visible region and in the UV region. Its optical properties were detected by UV spectroscopy. Strength properties such as light fastness, nitro resistance, alkali resistance, acid resistance, rub resistance, drying time, adhesion and dry film weight of the prints were determined. As a result; Inkjet ink with 1, 3, 6, 8-pyrene sulfonic acid tetrasodium salt was produced and it was concluded that it has good resistance properties.
Neighborhoods today emerges as “design incubators” as they are characterized by the proactivity of local actors — such as citizens, shopkeepers, associations, informal groups — acting at the core of the design process by developing brand-new and tailor-made solutions and at the same time provide environmental, economic, and social beneficial transformation in an inclusive and democratic way. This work presents considerations from a two-years initiative named Off Campus Nolo (OCN), a living lab promoted by the Politecnico di Milano that opened its doors in the Nolo neighborhood (Milan). With its rich set of contents (activities, projects, and events) the experience of OCN demonstrates how creating a bridge to transfer the academic skills on a neighborhood-community level can improve the quality of actions to be developed, also exploring new ways of spreading the knowledge from the academia and prompting new forms of social innovation within neighborhood communities.
This study conceives career development as a design process and not as a planning activity. An uncertain and fast-changing professional environment requires adaptation and training in a proper mindset. Since there is no such thing as “expertise” in life, Design methodologies and principles may be helpful for students to develop self-awareness and guidance. This study presents a comparative approach based on Beckman and Barry’s (2007) learning framework of the two main career development methodologies for students based on Design Thinking: “Designing Your Life and BE(A)ST” (BE Aware STudent). Designing Your Life explores design thinking principles and techniques to help individuals create fulfilling and meaningful careers. BE(A)ST is an approach, process, and set of tools that assist students in designing their careers while still at university.
Ellen Gonzalez, Francesca Zampollo, Manuela Quaresma
This conversation explores theory and practice in Food Design in a sustainable and systemic perspective, by integrating Food System Design models with examples from Bologna’s food landscapes. The case studies illustrate how deliberate design interventions across the food cycle can reshape food production, procurement, processing, consumption, and disposal, extending beyond edible products to encompass logistics, packaging, communication, and cultural practices. Zampollo’s Food System Design theory reinforces the role of designers and system thinkers as agents capable of promoting changes through conscious choices within communities. The intertwined components of society, education, sustainable best practices, governance and finance, technology, and territory are presented as the Circular Food System model—a paradigm for sustainable, equitable food practices. This model combines Gonzalez’s innovative framework with practical HoReCa (Hotel, Restaurant, and Catering) insights and academic perspectives in design and sustainability. The conversation underscores the designer’s role in actively setting a pathway toward sustainable and regenerative food systems by emphasizing systemic thinking and collaboration.
Meeting the needs of today’s industry plays a prominent role in the
progress and competitive strength of any country. Therefore, it is necessary to
align the curriculum of engineering courses with them. In this research, the focus
has been on the mechanical engineering curriculum, especially in the universities
of Iran. For this purpose, first by surveying the industry owners and reviewing the
literature, these expectations have been identified and prioritized. Accordingly, the
most important of these needs are creativity, visualization ability, familiarity with
manufacturing processes, and agility in learning new concepts. Then, using a twostage quality function deployment method (QFD), these expectations are translated
into curriculum specifications. The results show that the most effective groups of
courses in this field are elective courses, skill courses such as engineering graphics
(including technical drawing and drawing courses), design of machine components,
and practical workshops. In the existing programs, compared to courses in specialized
theory and basic courses, some of them have received less considerable attention in
quantity and quality
Special aspects of education, Engineering (General). Civil engineering (General)
Modern software-based systems operate under rapidly changing conditions and face ever-increasing uncertainty. In response, systems are increasingly adaptive and reliant on artificial-intelligence methods. In addition to the ubiquity of software with respect to users and application areas (e.g., transportation, smart grids, medicine, etc.), these high-impact software systems necessarily draw from many disciplines for foundational principles, domain expertise, and workflows. Recent progress with lowering the barrier to entry for coding has led to a broader community of developers, who are not necessarily software engineers. As such, the field of software engineering needs to adapt accordingly and offer new methods to systematically develop high-quality software systems by a broad range of experts and non-experts. This paper looks at these new challenges and proposes to address them through the lens of Abstraction. Abstraction is already used across many disciplines involved in software development -- from the time-honored classical deductive reasoning and formal modeling to the inductive reasoning employed by modern data science. The software engineering of the future requires Abstraction Engineering -- a systematic approach to abstraction across the inductive and deductive spaces. We discuss the foundations of Abstraction Engineering, identify key challenges, highlight the research questions that help address these challenges, and create a roadmap for future research.
Muhammad Tayyab Khan, Lequn Chen, Ye Han Ng
et al.
Geometric Dimensioning and Tolerancing (GD&T) plays a critical role in manufacturing by defining acceptable variations in part features to ensure component quality and functionality. However, extracting GD&T information from 2D engineering drawings is a time-consuming and labor-intensive task, often relying on manual efforts or semi-automated tools. To address these challenges, this study proposes an automated and computationally efficient GD&T extraction method by fine-tuning Florence-2, an open-source vision-language model (VLM). The model is trained on a dataset of 400 drawings with ground truth annotations provided by domain experts. For comparison, two state-of-the-art closed-source VLMs, GPT-4o and Claude-3.5-Sonnet, are evaluated on the same dataset. All models are assessed using precision, recall, F1-score, and hallucination metrics. Due to the computational cost and impracticality of fine-tuning large closed-source VLMs for domain-specific tasks, GPT-4o and Claude-3.5-Sonnet are evaluated in a zero-shot setting. In contrast, Florence-2, a smaller model with 0.23 billion parameters, is optimized through full-parameter fine-tuning across three distinct experiments, each utilizing datasets augmented to different levels. The results show that Florence-2 achieves a 29.95% increase in precision, a 37.75% increase in recall, a 52.40% improvement in F1-score, and a 43.15% reduction in hallucination rate compared to the best-performing closed-source model. These findings highlight the effectiveness of fine-tuning smaller, open-source VLMs like Florence-2, offering a practical and efficient solution for automated GD&T extraction to support downstream manufacturing tasks.
This project creates a visual-mental-physical circuit between a Generative Adversarial Network (GAN), a co-robotic arm, and a five-year-old child. From training images to the latent space of a GAN, through pen on paper to a live human collaborator, it establishes a series of translational stages between humans and non-humans played out through the medium of drawing. Trained on a subset of the Rhoda Kellogg Child Art Collection, the neural network at the center of this piece learns its own representations of these images. The generated results, synthetic children's drawings, are of interest both for being outside of adult conventions and learned expression-like Dubuffet's art brut or Surrealist automatism-and for how they align machine learning with the human act of learning to draw. The project layers many kinds of agency and embodiment: from the thousands of anonymous children who produced the original artwork used as training data, through the co-robot drawing from GAN-generated imagery, to the human child's active perception and graphic response to the robot. These questions of where we search for the other; when we attribute autonomy and intelligence; and why we might wish to escape our human subjectivities speak to core issues in the design and use of AI systems. This project is one attempt to think through those questions in an embodied way.
Silvira Trijayati, Jerry Kurniawan Tumewah, Arya Harditya
COVID-19 is a disease that has spread throughout the world and is transmitted through inhalation or contact with droplets of infected people. The Indonesian Government has established a health protocol to reduce the spread of COVID-19, which is checking the body temperature of visitors at public places. The officers' representatives from public places are mobilized to check the body temperature of the visitors by bringing the thermometer closer to the forehead or hand of the visitors. This paper aims to design a contactless thermometer using an Arduino Uno by adding an interactive design and light installation. It aims to enhance the user-experience rather the design idea itself. The thermometer will move a mechanical flower adjusted by the temperature measurement with this product design.
Alonso Camacho-Reyes, Jose Manuel Vasco-Olmo, Elias Lopez-Alba
et al.
In the present work, fatigue crack tip shielding influence is assessed via two full-field optical techniques which are thermoelastic stress analysis and digital image correlation. Two different crack tip field models (CJP and Muskhelishvili) were combined with experimental data from both optical techniques to determine the ΔK<sub>eff</sub>. The crack tip fields were measured on an aluminium alloy (7050-T6) specimen during fatigue crack growth testing for different R-ratios. The obtained results agree well in terms of ΔK<sub>eff</sub> showing a variation in ΔK as the R-ratio changes. Hence, the ability of both techniques and crack tip field models to measure effective fatigue crack driving forces is highlighted.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
Tirth Shah, Christian Brendel, Vittorio Peano
et al.
Mechanical vibrations are being harnessed for a variety of purposes and at many length scales, from the macroscopic world down to the nanoscale. The considerable design freedom in mechanical structures allows to engineer new functionalities. In recent years, this has been exploited to generate setups that offer topologically protected transport of vibrational waves, both in the solid state and in fluids. Borrowing concepts from electronic physics and being cross-fertilized by concurrent studies for cold atoms and electromagnetic waves, this field of topological transport in engineered mechanical systems offers a rich variety of phenomena and platforms. In this review, we provide a unifying overview of the various ideas employed in this area, summarize the different approaches and experimental implementations, and comment on the challenges as well as the prospects.
In intelligent manufacturing, the quality of machine translation engineering drawings will directly affect its manufacturing accuracy. Currently, most of the work is manually translated, greatly reducing production efficiency. This paper proposes an automatic translation method for welded structural engineering drawings based on Cyclic Generative Adversarial Networks (CycleGAN). The CycleGAN network model of unpaired transfer learning is used to learn the feature mapping of real welding engineering drawings to realize automatic translation of engineering drawings. U-Net and PatchGAN are the main network for the generator and discriminator, respectively. Based on removing the identity mapping function, a high-dimensional sparse network is proposed to replace the traditional dense network for the Cyclegan generator to improve noise robustness. Increase the residual block hidden layer to increase the resolution of the generated graph. The improved and fine-tuned network models are experimentally validated, computing the gap between real and generated data. It meets the welding engineering precision standard and solves the main problem of low drawing recognition efficiency in the welding manufacturing process. The results show. After training with our model, the PSNR, SSIM and MSE of welding engineering drawings reach about 44.89%, 99.58% and 2.11, respectively, which are superior to traditional networks in both training speed and accuracy.
Background: Software development results in the production of various types of artifacts: source code, version control system metadata, bug reports, mailing list conversations, test data, etc. Empirical software engineering (ESE) has thrived mining those artifacts to uncover the inner workings of software development and improve its practices. But which artifacts are studied in the field is a moving target, which we study empirically in this paper.Aims: We quantitatively characterize the most frequently mined and co-mined software artifacts in ESE research and the research purposes they support.Method: We conduct a meta-analysis of artifact mining studies published in 11 top conferences in ESE, for a total of 9621 papers. We use natural language processing (NLP) techniques to characterize the types of software artifacts that are most often mined and their evolution over a 16-year period (2004-2020). We analyze the combinations of artifact types that are most often mined together, as well as the relationship between study purposes and mined artifacts.Results: We find that: (1) mining happens in the vast majority of analyzed papers, (2) source code and test data are the most mined artifacts, (3) there is an increasing interest in mining novel artifacts, together with source code, (4) researchers are most interested in the evaluation of software systems and use all possible empirical signals to support that goal.